Health Catalyst, Inc (HCAT) Fair Value & Analysis
Healthcare · US · Market cap $129M
Fair value as of: Jun 25, 2026
Analysis
Health Catalyst, Inc (HCAT) currently trades at $1.72, while our model-based Fair Value estimate is $1.10 — implying the stock looks roughly 36.0% overvalued today. We read business quality at 95/100 (high quality), in the Healthcare sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: low).
About the company
Health Catalyst, Inc. provides data and analytics technology and services to healthcare organizations in the United States. The company operates in two segments: Technology and Professional Services. It offers ignite data and analytics platform that provides clients a single comprehensive environment to integrate and organize data from their disparate software systems; and applications, a software analytics applications build for ignite platform to analyze clients face across clinical improvement, revenue and cost improvement, ambulatory operations, measures and registries, and data and analytics. The company also provides expertise solutions comprising data and analytics, domain expertise and education, tech-enabled managed, and implementation services; and opportunity analysis and prioritization, data governance, data modeling and analysis, quality and process improvement strategy, cost accounting, data abstraction, and population health strategies. It serves academic medical cent…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.